A scalable network forensics mechanism for stealthy self-propagating attacks

Network forensics supports capabilities such as attacker identification and attack reconstruction, which complement the traditional intrusion detection and perimeter defense techniques in building a robust security mechanism. Attacker identification pinpoints attack origin to deter future attackers, while attack reconstruction reveals attack causality and network vulnerabilities. In this paper, we discuss the problem and feasibility of back tracking the origin of a self-propagating stealth attack when given a network traffic trace for a sufficiently long period of time. We propose a network forensics mechanism that is scalable in computation time and space while maintaining high accuracy in the identification of the attack origin. We further develop a data reduction method to filter out attack-irrelevant data and only retain evidence relevant to potential attacks for a post-mortem investigation. Using real-world trace driven experiments, we evaluate the performance of the proposed mechanism and show that we can trim down up to 97% of attack-irrelevant network traffic and successfully identify attack origin.     

The use of mobile technology for online shopping and entertainment among older adults in Finland

Older adults are becoming an important market segment for all internet-based services, but few studies to date have considered older adults as online shoppers and users of entertainment media. Utilising the concept of life course, this article investigates the use of mobile technologies for online shopping and entertainment among consumers aged 55 to 74. The data were collected with a web-based survey completed by a panel of respondents representing Finnish television viewers (N = 322). The results reveal that consumers aged 55 to 74 use a smartphone or tablet to purchase products or services online as often as younger consumers. In contrast, listening to internet radio and watching videos or programmes online with a smartphone or tablet are most typical for younger male consumers. The results demonstrate that mobile-based online shopping is best predicted by age, higher education, and household type (children living at home), and use of entertainment media by age and gender.     

计算机取证中的异常文件发现

在计算机取证中,寻找证据的过程是最耗费时间的一个阶段,是计算机取证自动化的瓶颈。面对海量的数据信息,如何确定哪些是犯罪证据,并更快更准确地找到这些证据,是摆在每一个计算机取证者面前的难题。为了解决这一问题,提出了一种取证目标自动确定的新方法,通过孤立文件检测法找出安全事件中产生的异常文件。实验结果表明,这种方法能快速找出系统中隐藏的异常文件,加快证据搜索的速度,进而提高整个计算机取证工作的效率。     

Digital image analysis of gunshot residue dimensional dispersion by computer vision method

Detection and identification of gunshot residues (GSR) have been used as base evidence in elucidating forensic cases. GSR particles consist of burnt and partially unburned material and contaminate the hands, face, hair, and clothes of the shooter when coming out of the gun. Nowadays, GSR samples are collected from the hands of the suspect and are analyzed routinely in forensic laboratories by the scanning electron microscope/energy dispersive spectroscopy (SEM/EDS) method. GSR particles are comprised of a morphological and specific structure (generally spherical and have a diameter between 0 and 100 μm [occasionally even larger]). In addition, the present studies in the field have claimed that GSR particles during formation are formed under equilibrium surface distribution and are unrelated to morphological dimensional classification. Our contribution to this study is two-folded. First, this study offers a new approach to identify images of GSR particles by computer vision gathered by SEM/EDS method from the hand of the shooter. Second, it presents open access to the SEM/EDS image data set of the analyzed GSR. During the study, a new data set consisting of 22,408 samples from three different types of MKEK (Mechanical and Chemical Industries Corporation) brand ammunition has been used. It is seen in the results that the computer vision method has been successful in the dimensional classification of GSR.     

State of the art and future developments of measurement applications on smartphones

The modern smartphones contain different sensor technologies, so they can be used as stand-alone measurement instruments on a wide range of application domains. The paper deals with a survey of measurement applications based on smartphones. In the first part, the evolution of mobile phone technologies, including the sensors and mobile networks developments, is presented. Then, in order to highlight the sensors and the communication capabilities, the architectural overview of the hardware and software technologies, which are available on latest series of smartphones, is reported and discussed. A review of measurements applications using the smart sensors and the communication interfaces available on smartphones, it is also presented. A classification of smartphone applications, which looks the smartphone as a handheld measurement instrument, is presented. In the last part, the integration of augmented reality to the measurement applications and new type of measurement systems, having a smartphone as processing support, is presented.     

智能手机操作系统群雄并起

近年来,随着全球移动数据业务使用量的迅猛增长,智能手机销量不断攀升。代表不同市场阵营的智能手机操作系统竞争日益激烈。笔者在回顾市场上主流操作系统形成现今市场地位的历史原因同时,对其未来的发展机遇逐一作了分析,在此基础上,对未来智能手机操作系统的市场格局做出了预测。     

基于手机条码识别的物联网设计

随着移动互联网时代的来临,智能手机已成为物联网时代一个标志性的移动终端工具,在Android开源智能手机操作系统下,研究了二维条码编解码,模拟生成了两维条码图片,研究表明Android开源智能操作系统在物联网的应用中有广泛的应用前景.     

一种新的基于DCT域系数对直方图的图像篡改取证方法

提出了一种基于离散系数变换(DCT)域系数对直方 图特征的图像篡改取证方法。首先对图像进行 DCT,并在给定的阈值下,对变换后的DCT系数进行系数对直方图化;而后对直方图化后 的值进行归一化处理,再用主成分分析(PCA)对上述数据进行降维处理取得系数对直方图特 征;最后将真 实图像和篡改后图像的系数对特征用支持向量机(SVM)进行分类识别。实验结果证明,和现 有的一些算 法相比,提出的方法计算复杂度低,在CASIA v1.0平均识别率为97.92%,CASIA v2.0平均 识别率为91.20%,对未压缩图像和压缩图像的拼接篡改都具有良好的 识别性能。     

GIS定位分析平台助力运营商快速发现定位伪基站

伪基站成为不法分子实施电信诈骗和非法广告推销等违法犯罪活动的工具,严重损害了群众财产权益、侵犯了公民隐私、扰乱了国家通讯秩序和社会公共秩序。北京中创信测科技股份有限公司陈江东所撰《GIS定位分析平台助力运营商快速发现定位伪基站》一文从描述伪基站的工作原理入手,着重介绍了中创信测的伪基站GIS定位分析平台,该平台的功能特点为运营商鉴别、了解并快速定位伪基站提供了工具和手段,可供相关技术人员参考、借鉴。